Computational Scientist - Genomic Medicine

M. D. Anderson Cancer Center's research community provide vast opportunities for computational biologist to work closely with clinicians/biologists on various projects with scientific or clinical focuses. M. D. Anderson's Big Data analytic programs also has accumulated patients' clinical and genomic data to be mined to drive translational research and ultimately improve patient outcomes. The department of Genomic Medicine has openings for computationally trained scientists with desires of applying cutting edge analytical tools to analyze large scale genomic data and gaining in depth knowledge of cancers. The computational scientists are expected to be actively involved in research projects and are also encouraged to initiate independent studies mining the existing data. The computational scientists are required to participate and reach out to biologists/clinicians to brain storm ideas and hypotheses, present scientific findings in project meetings and conferences, and publish in scientific journals. The Department of Genomic Medicine has ongoing collaborations with researchers across departments and institutions. The computational genomics scientists will serve as computational experts throughout proposal/grant application and execution of experiments, lead the efforts of data analysis and interpretation, and actively participant in report and manuscript writing.

Key Functions

1. Actively involved throughout projects by leading data analysis/interpretation, communicating with project leaders about significant scientific findings and clinical applications of the results, preparing manuscripts and reports for publications and professional meetings, and providing expert advises on experimental design, data collections strategies, and statistical analysis.

2. Conduct independent researches by mining large scale data to produce results of clinical and scientific significance. Communicate with biologists and clinicians to formulate questions/ hypotheses that can be answered/tested by querying data repositories.

3. Develop analytical and visualization tools to enhance user access and utilizations of MDACC's data repository. Implement computational tools to systematically explore and mine internally or publically available multi-dimensional data using advanced analytical tools to derive meaningful insights of the data, discuss the results with biologists/clinicians to provide guidance in their studies, formulate hypothesis of scientific and clinical relevance, and design and conduct further studies to confirm/validate the findings

4. Identify issues of practical or theoretical importance and then conduct independent studies to derive solutions through innovative mathematical/computational approaches. Publish the results in scientific journals and present the results in professional conferences.

5. Develop software modules following sound software engineering practices to be easily added to an automated production data processing/analysis pipeline or to provide visualization of data stored in internal databases.

5. Integrate genomic data generated in house and those available publically, checking the quality and integrity of the data, and import them into internal data portal for query and data mining.

6. Evaluate existing computational algorithms and develop new algorithms that can be used internally by researchers within MDACC or in larger research communities.

Core Competencies:

1. Self-Motivation (Operative/Team Support): Set high standards of performance; pursue goals with energy and persistence; drive for results and achievement.
   • Use standards set by management. Take ownership for actions. Continually meet departmental goals.

1. Technical/Functional Expertise (Operative/Team Support): Demonstrate technical proficiency required to do the job; possess up-to-date knowledge in the profession; provide technical expertise to others.
   • Apply basic technical/functional knowledge to complete work. Meet essential position requirements.

1. Analytical Thinking (Operative/Team Support): Gather relevant information; systematically break down problems into simple components; make sound decisions.
   • Recognize simple cause and effect relationships. Diagnose problems by breaking them down into simple tasks or activities.

1. Team with Others (Independent Contributor): Encourage collaboration and input from all team members; value the contributions of all team members; Balance individual and team goals.
   • Support and show respect to team members. Recognize how individual actions affect the team.
   • Model team qualities, i.e. respect, helpfulness and coping. Support team decisions once they are made and help to implement.

Ideal candidate will have experience in data analysis and scientific software development and relevant research experience pertaining to platform. Working experience in mining genomic and clinical data. Applicants with experience in pattern recognition/machine learning, mathematical/statistical modeling, network analysis and experience in data integration, data mining, NGS data analysis (mutations, structural variations, and expression). Proficiency in at least one programming language such as R, C/C++, Perl, Python, or JAVA.

Working Conditions

Laboratory environment

This position requires:

Working in Office Environment

____No

__X_ Yes

Working in Patient Care Unit (e.g. Nursing unit; outpatient clinic)

_X_ No

____ Yes

Exposure to human/animal blood, body fluids, or tissues

__X__No

__ Yes

Exposure to harmful chemicals

__X__No

___ Yes

Exposure to radiation

_X_ No

____ Yes

Physical Demands

Indicate the time required to do each of the following physical demands:

Time Spent

Never

0%

Occasionally

1-33%

Frequently

34-66%

Continuously

67-100%

Standing

Walking

Sitting

Reaching

Lifting/Carrying

Up to 10 lbs.

10lbs to 50 lbs.

More than 50 lbs.

Pushing/Pulling

Up to 10 lbs.

10lbs to 50 lbs.

More than 50 lbs.

Use computer/keyboard

EDUCATION:
Required: Bachelor's degree in Biomedical Engineering, Electrical Engineering, Physics, Applied Mathematics or related field.

Preferred: Master's degree or PhD with a concentration in Science, Engineering or related field.

EXPERIENCE:
Required: Five years experience in scientific software development/analysis. With preferred degree three years experience required.

Preferred: Experience in data analysis and scientific software development and relevant research experience pertaining to platform. Working experience in mining genomic and clinical data.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html